Schedule

Enjoy breakfast at your hotel while vendor tables and posters are set up in the Slate.

With Tom Lewis of Guide Dogs UK. It is a widely known principle that inbreeding is detrimental to health. However, the general understanding of the complexities of inbreeding, and its opposite - maintenance of genetic diversity, is often patchy. Some degree of inbreeding is unavoidable given finite populations and also is a consequence of genetic selection for improvement of traits of interest. Thus it is the management of inbreeding, or the rate of loss of genetic diversity, to sustainable levels in populations that is critical. In this talk the topics of how inbreeding is defined, the problems it may cause and how it is measured using pedigree information will be briefly discussed. The parameters rate of inbreeding and effective population size will be introduced, and their relevance illustrated with examples from population analysis of Kennel Club registered populations.

Presented by Heather Huson of Cornell University. Genomic estimated breeding values (gEBVs) are statistically calculated numbers that estimate a dog’s potential for health, conformation, and behavior traits based on their DNA profile. They allow for more accurate selection and refined management of working dogs which increases the rate of change achievable in selection programs to improve overall working dog success rates. Modern quantitative and statistical genetic methods allow the prediction of breeding values by correlating phenotypic data on health, conformation, and performance traits with genomic markers, specifically single nucleotide polymorphisms (SNPs). These correlations are used to generate predictive algorithms based on a reference population with known genotypic and phenotypic information. These algorithms are then used to predict merit or phenotypic expression of individuals related to the reference population (same species or breed) by using the established relationship between genetic markers and phenotype. To this end, a reference population continues to be developed for prediction algorithms of over 54 health and performance traits. The well-established genomic prediction model, GBLUP, was identified as similarly accurate and more computationally efficient than four machine learning models assessed. Trait prediction was explored in a large cohort of guide dogs and another cohort of personally owned competitive sled dogs allowing us to evaluate our ability to predict traits in a large, single-managed breeding colony using standardized protocols, along with client-owned dogs, scored by their trainers on a prescribed set of traits. Heritability and prediction accuracy varied among traits and datasets comparing the sled and guide dogs and within the guide dogs, the different breeds. Indexes, where multiple traits are combined into a single selection value (ie. health index), were also created, to improve ease of selection. In all, our goal is to build a tool for breeding selection and training management that will improve overall working dog success rates. Here, we explain how genomic prediction works, its utility in working dog management, and the progress our research has made in working dog genomic prediction. We highlight successes, including prediction model optimization and predicted traits, as well as challenges and future directions.

Presented by Frances Chen. Many canine cancers share genetic and environmental risk factors with human cancers, while their shorter lifespans enable longitudinal studies linking risk factors with cancer outcomes. This positions dogs as invaluable models for comparative and translational cancer research. DNA sequencing has been a transformative approach in cancer research, offering an opportunity to identify genetic variants associated with risk and target pathways for new therapies. Beyond research discovery, genomic data unlocks the potential for genomic selection as an approach to reduce heritable cancer risk in dogs. While genomic selection using genomic estimated breeding values (GEBVs) has been a proven, powerful approach in livestock, its potential has yet to be explored in dogs. Leveraging DNA sequence data and longitudinal cancer outcomes from the Golden Retriever Lifetime Study and the International Working Dog Registry (IWDR), we have investigated inherited risk for canine hemangiosarcoma and provided initial evaluation of the feasibility of genomic selection in at-risk Golden Retrievers. In collaboration with IWDR, we are integrating estimated breeding values (EBVs) for hemangiosarcoma into working dog breeding programs to reduce disease incidence over time. To accelerate the collection of genomic data needed for GEBVs, we have partnered with Gencove to offer a targeted capture panel for working dog populations. This tool offers high-accuracy genotyping for key trait-associated loci while incorporating whole-genome sequencing. It allows breeding programs to integrate collection of genomic data into their workflows for routine genetic testing, thereby laying the foundation for genomic selection tailored to their goals. By aligning genomic discovery with practical selection strategies, this project aims to establish proof of concept that genomic EBVs can facilitate genetic selection against canine hemangiosarcoma while deepening our understanding of cancer genetics in both dogs and humans. Our collaboration with IWDR enables direct engagement with working dog organizations, laying the groundwork for integrating genomic tools into breeding programs to enhance the health and welfare of working dogs while driving discovery in cancer research for their human companions.

Presented by Per Arvelius of the IWDA board. Dogs have proven to be enormously useful for military and police work. However, animals well suited for these tasks have since long been in short supply worldwide. To function well in service, dogs are required to be both healthy and mentally strong. The latter typically requires high levels of confidence (nerve stability, hardness, courage) and engagement (competitiveness, hunting drive, prey drive, liveliness). These traits often make the dogs demanding to handle, and less suited outside a professional working environment. Naturally, hobby breeders usually have other breeding goals than what is optimal for service. Furthermore, setting up and running a breeding program takes a long time and requires substantial investments, and the market is unstable. The consequence is that few, if any, large commercial breeding programs exist. Only occasionally, governmentally financed organisations set up breeding programs large enough to allow for systematic selection of new breeding animals among the dogs produced, thereby making possible a genetic progress without unreasonable inbreeding-related risks. The few programs that have existed were typically shut down within one or few decades, also when they were successful. The reason was usually decision makers lacking knowledge and engagement, or not having enough sense of long-term responsibility versus short-term savings. The fact that the very same mistake of cancelling well-run breeding programs happens over and over again, resulting in a decreased capacity for military and police organisations, calls for actions to prevent it from continuing to happen. An organisation such as IWDA can play a role in such actions by, for example, providing best practice and scientifically based information directed at decision makers; facilitating collaborations between breeding programs; arranging platforms for education, discussion and exchange of experience among breeding managers; advocating the essential importance of involving animal breeding expertise.

Presented by Karen Overall of UPEI. The lifetime prevalence of behavioral concerns in dogs has been shown to be as high at 99%. Some common behavioural pathologies (eg, fears and phobias of noises) have a lifetime prevalence of 50%. Early data collected by Scott, Fuller and colleagues in the 1960s and 1970s using exclusional or deprivational experiments with multiple litters of 5 similarly shaped/sized breeds across breed groups established limits for the ends of the sensitive periods for social and environmental exposure. However, we still lack criteria to define and quantify normal behavior and so cannot identify and quantify early deviations from it. We also lack standardized assessments to evaluate risk factors and their effects on behaviour.

Presented by Laura Edwards of Sunrise Service Dogs. The success of working dog programs across both government agencies and service dog organizations relies critically on accessing high-quality canines with specific traits and capabilities. This presentation examines the intersection of breeding partnerships that serve multiple sectors, from law enforcement and detection work to service and guide dog programs, offering valuable insights from diverse successful collaborations with private breeders across international markets. Drawing from real-world examples from private breeders that supply dogs to government agencies (including police K9 units, conservation detection teams, and search and rescue operations) as well as established service dog organizations like Sunrise Service Dogs, we will explore how different sectors can adapt and apply proven partnership strategies. The discussion will highlight how successful breeding programs navigate varying requirements while maintaining consistent quality across different working dog disciplines. Key Topics: - Comparative selection criteria between government/detection work and service dog programs - International case studies of breeders successfully serving multiple sectors - Specialized health and temperament considerations for different working roles - Cross-sector quality assurance protocols and standards - Contractual frameworks that accommodate various program needs - Expectations and reciprocal responsibilities in breeder-program partnerships

Presented by Dr Lorna Irish.

Presented by Simon Gadbois of Dalhousie University. In this theoretical and methodological talk, I will examine two traditional methodologies often used with scent dogs: 1) In field work, the use of transects (especially with conservation canines). Here, ethology and sensory ecology can contribute some insight. We will discuss the problems with transects (for the dogs), and the “natural” alternative. 2) In lab work, especially in biomedical detection, for mostly historical reasons, scent training with canines has used the mAFC model, i.e., forced choice tasks (i.e., line-ups, wheels, carousels). Robust data from psychophysics would suggest an alternative, if not a replacement, depending on the goal of the study: “true” detection. I say true detection (which includes yes/no and go/no-go procedures) because mAFC tasks are actually discrimination tasks. In some applications, such as for alert, or even for a clear idea on performance in diagnostic work, there is a strong argument to at least use discrimination (mAFC) and detection in tandem, if not detection alone. I will present arguments from Signal Detection Theory that will demonstrate that such a methodology provides significantly more information about the dog’s performance (accuracy and precision), especially if combined, by addressing both sensitivity (detection task) and specificity (discrimination task).

Presented by Scott Bruce, New Zealand Police Dog Section. Optimising Police Dog Breeding and Development for Operational Performance: Required outcomes and the impact of genetics, the shaping of Central Nervous System responses and early behavioural development. The New Zealand Police Dog Section breeds and develops approximately 100 German Shepherds and 30 Labrador Retrievers annually, selecting for essential traits such as hunt drive, nerve strength, and the ability to bite and grip to ensure their success in high-intensity environments. Evolving operational demands of policing require refining breeding, behavioural development, and training methodologies to optimise operational effectiveness. This presentation focuses on the optimal characteristics of a successful Police dog for operational duties and on the indicators impacting this success: (1) genetic potential within working dog lineages, (2) the Central Nervous System in shaping genetic potential, and (3) the impact of early behavioural development and training on mindset and physiological reactivity. By understanding and tracking these indicators we can optimize genetic selection, neurological function, and behavioral conditioning to achieve the essential operational traits of a high performing Police dog.

Presented by Dave Roberts. How to use AI to help with the human animal bond is not just an intellectual exercise. In this presentation, learn how researchers leveraged knowledge of dog training and behavior to develop new algorithms and technologies.

Presented by Dr Claire Guest OBE. Throughout history, dogs have fulfilled a range of different functions and canine roles have developed to include medical support and disease detection tasks, with growing evidence of elevated levels of a ‘signature’ volatile organic compound (VOCs) associated with disease. Medical Detection Dogs (MDD) charity, a pioneer of both medical assistance and remote disease detection remains committed to carrying out empirical research to improve operations, inform future medical technologies and improve the understanding of our relationship with dogs. Our Medical Alert Assistance Dogs use olfaction to alert and thereby provide day-to-day support for people living with life threatening conditions. Historically, most of our dogs were trained to alert to blood sugar changes for people living with Type 1 diabetes, but increasingly we place dogs with individuals with Postural Tachycardia Syndrome (PoTS) and other cardiac conditions including non-epileptic attack disorder and Addison’s disease. Our ongoing monitoring suggests high levels of alerting accuracy and highly intuitive behaviours demonstrated by the dogs in partnerships. In addition, MDD have worked on NHS-approved clinical trials, exploring dogs’ ability to detect cancer, the malaria parasite, Parkinson’s disease, bacteria, and COVID-19. As medical usage expands, it is imperative that the value of our dogs is objectively assessed, and their potential capabilities are optimised to further disease diagnostics. To better understand canine decision making, MDD works together with the Animal Computer Interaction Lab, (Open University), using technology which enhances the dog’s ability to communicate their degree of certainty when detecting disease from presented samples. This assists the interpretation of equivocal behaviours where the decision of the dog is unclear, and gives the dog an interface to provide further information to the handler.

Presented by Kat Janczur of Canine Detection Solutions. Detection dogs are increasingly used in conservation efforts to find endangered and invasive species; effective detection is crucial for the implementation of successful management techniques. Due to our experience with training dogs to detect Japanese knotweed (Reynoutria japonica) we were asked to explore training for another; this time elusive plant (which cannot be named at this time). Presence of this plant can be a good predictor of rich biodiversity and therefore environment that needs to be protected. In this presentation we will discuss the challenges that come with training dogs to detect living plants. Whether working with invasive or endangered species acquiring training samples can be very difficult and those limitations have to be considered during training, especially the imprinting stage. Another important issue to consider is the discrimination neccesary when our target is mixed with its environment is the discrimination. In both the case of Japanese knotweed and the other plant there are other species that are closely related to them that may have similar scent profile and we therefore have to make sure dogs have a good understanding of what they are searching for.

Presented by Irit Gazit, SpotitEarly LTD. Early detection of malignancies significantly enhances survival rates, minimizes the need for prolonged and invasive treatments, and reduces healthcare costs. SpotitEarly Ltd. has developed a simple, non-invasive, and self-administered screening method to detect cancer in exhaled breath samples from humans. This screening technology combines canine detection with artificial intelligence (AI). The technology relies on three principles: the distinct molecular profile of cancer in breath samples, the canines’ odor sensory abilities to detect this molecular profile, and the use of AI for analyzing canines’ input to determine the presence of cancer.

Enjoy a 3 course dinner in the Slate, transformed into a delightful restaurant for the evening, with live entertainment included!